Assessment of the Impact of Climate Change on the Ecological Resilience of the Yangtze River Economic Belt

With climate change and frequent extreme weather events, ecological stability is facing threats. This study constructs a quantitative assessment model coupling climate change and ecological resilience (ER), explores the impact of future climate change on ER, and identifies key meteorological risks that affect ER. Taking the Yangtze River Economic Belt (YREB) as the research area, the main research results are as follows: (1) Under the four future scenarios, the Climate Change Impact Index (CCI) values for ER are −0.8005, −0.8924, −0.9540, and −1.2298, respectively, indicating a general decline in ER across the YREB. (2) The extent of climate change impacts varies significantly among scenarios, with the ranking SSP5-8.5 > SSP4-6.0 > SSP2-4.5 > SSP1-2.6. The SSP5-8.5 scenario exhibits the most severe impacts, with CCI values of −0.7015, −1.2910, −1.3124, and −1.6144. (3) Spatially, climate change exerts the greatest impact on the upstream regions, followed by the downstream and midstream areas. Among these, very high resilience and very low resilience levels experience the most pronounced changes. (4) Temperature (Temp) and the Normalized Difference Vegetation Index (NDVI) are the main meteorological risks for the deterioration of ER. In future scenarios, Temp demonstrates an increasing trend while NDVI shows a significant decline.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-09-15
DOI
https://doi.org/10.3390/su17188265
Citations
1
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
1.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of the Impact of Climate Change on the Ecological Resilience of the Yangtze River Economic Belt

Feng Yan, Jincao Yao, Hongliang Wu
1 citations
Sustainability
Land Use and Ecosystem Services
1.11
article

Assessment of the Impact of Climate Change on the Ecological Resilience of the Yangtze River Economic Belt

Feng Yan, Jincao Yao, Hongliang Wu
article en
1 citations

Abstract

With climate change and frequent extreme weather events, ecological stability is facing threats. This study constructs a quantitative assessment model coupling climate change and ecological resilience (ER), explores the impact of future climate change on ER, and identifies key meteorological risks that affect ER. Taking the Yangtze River Economic Belt (YREB) as the research area, the main research results are as follows: (1) Under the four future scenarios, the Climate Change Impact Index (CCI) values for ER are −0.8005, −0.8924, −0.9540, and −1.2298, respectively, indicating a general decline in ER across the YREB. (2) The extent of climate change impacts varies significantly among scenarios, with the ranking SSP5-8.5 > SSP4-6.0 > SSP2-4.5 > SSP1-2.6. The SSP5-8.5 scenario exhibits the most severe impacts, with CCI values of −0.7015, −1.2910, −1.3124, and −1.6144. (3) Spatially, climate change exerts the greatest impact on the upstream regions, followed by the downstream and midstream areas. Among these, very high resilience and very low resilience levels experience the most pronounced changes. (4) Temperature (Temp) and the Normalized Difference Vegetation Index (NDVI) are the main meteorological risks for the deterioration of ER. In future scenarios, Temp demonstrates an increasing trend while NDVI shows a significant decline.

SustainabilityVol. 17(18)
Nanchang University (CN), PowerChina (China) (CN), Powerchina Huadong Engineering Corporation (China) (CN)
Openalex Percentile: Top 20%
Land Use and Ecosystem Services
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.